Efficient Bayesian Phase Estimation
classification
🪐 quant-ph
keywords
phasedirectlyefficientestimationexperimentaladaptivealgorithmalgorithms
read the original abstract
We provide a new efficient adaptive algorithm for performing phase estimation that does not require that the user infer the bits of the eigenphase in reverse order; rather it directly infers the phase and estimates the uncertainty in the phase directly from experimental data. Our method is highly flexible, recovers from failures, and can be run in the presence of substantial decoherence and other experimental imperfections and is as fast or faster than existing algorithms.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
When Noisy Quantum Order Finding Remains Recoverable for Shor's Algorithm
Empirical study of real NISQ order-finding data identifies dominant verified mass fraction as the strongest predictor of whether standard post-processing recovers the true order.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.